TY - JOUR
AU - Attanasio,Orazio P.
AU - Banks,James
AU - Meghir,Costas
AU - Weber,Guglielmo
TI - Humps and Bumps in Lifetime Consumption
JF - National Bureau of Economic Research Working Paper Series
VL - No. 5350
PY - 1995
Y2 - November 1995
DO - 10.3386/w5350
UR - http://www.nber.org/papers/w5350
L1 - http://www.nber.org/papers/w5350.pdf
N1 - Author contact info:
Orazio Attanasio
Department of Economics
University College London
Gower Street
London WC1E 6BT
UNITED KINGDOM
Tel: 44/20-76795880
Fax: 44/20-79162775
E-Mail: o.attanasio@ucl.ac.uk
James Banks
Arthur Lewis Building-3.020
School of Social Sciences
The University of Manchester
Manchester M13 9PL
United Kingdom
E-Mail: j.banks@ifs.org.uk
Costas Meghir
Department of Economics
Yale University
37 Hillhouse Avenue
New Haven, CT 06511
Tel: 203/432-3558
E-Mail: c.meghir@yale.edu
Guglielmo Weber
University of Padua
Dipartimento di Scienze Economiche
Via del Santo 33, I-35123
Padova, ITALY
Tel: 39-049-8274271
Fax: 39-049-8274221
E-Mail: guglielmo.weber@unipd.it
AB - In this paper we argue that once one departs from the simple classroom example, or `stripped down life-cycle model,' the empirical model for consumption growth can be made flexible enough to fit the main features of the data. More specifically, we show that allowing demographics to affect household preferences and relaxing the assumption of certainty equivalence can generate hump-shaped consumption profiles over age that are very similar to those observed in household-level data sources, without appealing to alternative explanations (such as liquidity constraints, myopia or mental accounting). The hump-shape is partly attributable to precautionary savings, and partly due to demographics; the tracking (whereby consumption jumps with income) is instead due to the permanent nature of the income shocks. We use US household-level data to estimate preference parameters and income profiles, and then simulate consumption profiles for different education groups. Our simulated profiles show that the key features observed in the data can be closely matched in simulation. We also show that neglecting uncertainty produces consumption profiles that are `too flat,' whereas neglecting demographics generates consumption profiles that peak `too late.'
ER -